As part of our May Momentum campaign, we are excited to share an interview with Chris Armstrong, PhD, and post-doctoral researcher, Kathy Huang, PhD, about their ongoing ME/CFS research.
Please consider making a donation today to support our ongoing research efforts and bring us closer to finding effective diagnostics and treatments for millions worldwide. Every contribution, big or small, makes a significant impact!
Refining a Diagnostic Model and Designing a New PEM Project
The Heart of the Matter
- Dr. Chris Armstrong, the Director of the Melbourne ME/CFS Collaboration, recently interviewed his post-doc, Kathy Huang, PhD, about their work in ME/CFS. Watch the video here.
- After publishing an ME/CFS diagnostic model in November 2024, the team is conducting further work, trying to refine and improve the model, which places the project in the “Data Analysis” stage of the research process.
- This follow-up work includes looking at the model’s health factors in medical records to try to lead to earlier diagnosis of ME/CFS.
- In addition, the team is designing a new project focused on predicting post-exertional malaise (PEM) events and their duration and severity.
- The PEM project is being submitted for ethics review, so it is in the “Study Design, IRB/Ethics Review” stage of the research process.
Refining a Diagnostic Model and
Designing a New PEM Project
In November 2024, the Director of the Melbourne ME/CFS Collaboration, Dr. Chris Armstrong, and his team published a paper on a diagnostic model identifying ME/CFS from comorbid conditions. If you missed it, you can read more about that paper here. Dr. Armstrong and his post-doctoral student working on the project, Kathy Huang, PhD, recently sat down to talk about that study and what else she’s working on in ME/CFS.
The initial diagnostic model published by Dr. Armstrong’s team utilized 28 health factors, including patient-reported outcomes and metabolomics, to identify ME/CFS with 83% accuracy. While that work has been published, the team is now conducting follow-up work, putting the project in the “Data Analysis” stage of the research process.
The main objectives of the follow-up work are to improve the classification rate and refine the health factors needed for diagnosis. The team will also take a retrospective look at medical records to identify how often the health factors appear early on in the disease. Ideally, routine clinical information like some of these health factors could be used to diagnose ME/CFS earlier on in the disease trajectory.
One of the limitations of using data from the UK Biobank is that the health factors are from a single time point and require going to a clinic for assessment. Therefore, the team is also pursuing a new project that will be more accessible for people who are homebound.
By analyzing physiological data and biometric data, the team hopes to develop a method for predicting post-exertional malaise (PEM) events, including how long they will last and their severity. Importantly, this study will analyze naturally occurring PEM rather than induced PEM, and try to determine how far in advance they can detect the onset of a PEM event using wearables.
The team is submitting this new project for ethics review, which places it in the “Study Design, IRB/Ethics Review” stage of the research process.
Watch the full interview to hear about these projects from the study team.
